Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use penscola/tweet_sentiments_analysis_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use penscola/tweet_sentiments_analysis_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="penscola/tweet_sentiments_analysis_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("penscola/tweet_sentiments_analysis_bert") model = AutoModelForSequenceClassification.from_pretrained("penscola/tweet_sentiments_analysis_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 3
Browse files
pytorch_model.bin
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runs/Jul23_06-45-46_30fb4c0892ab/events.out.tfevents.1690094767.30fb4c0892ab.190.0
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